{"id":"https://openalex.org/W3173187313","doi":"https://doi.org/10.1140/epjds/s13688-021-00288-5","title":"Multilayer networks for text analysis with multiple data types","display_name":"Multilayer networks for text analysis with multiple data types","publication_year":2021,"publication_date":"2021-06-28","ids":{"openalex":"https://openalex.org/W3173187313","doi":"https://doi.org/10.1140/epjds/s13688-021-00288-5","mag":"3173187313"},"language":"en","primary_location":{"id":"doi:10.1140/epjds/s13688-021-00288-5","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00288-5","pdf_url":"https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds/s13688-021-00288-5","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds/s13688-021-00288-5","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Charles C. Hyland","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":true,"raw_author_name":"Charles C. Hyland","raw_affiliation_strings":["School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Yuanming Tao","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Yuanming Tao","raw_affiliation_strings":["School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Lamiae Azizi","orcid":null},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Lamiae Azizi","raw_affiliation_strings":["School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Martin Gerlach","orcid":null},"institutions":[{"id":"https://openalex.org/I4210126245","display_name":"Wikimedia Foundation","ror":"https://ror.org/032q98j12","country_code":"US","type":"nonprofit","lineage":["https://openalex.org/I4210126245"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Martin Gerlach","raw_affiliation_strings":["Wikimedia Foundation, San Francisco, USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wikimedia Foundation, San Francisco, USA","institution_ids":["https://openalex.org/I4210126245"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Tiago P. Peixoto","orcid":null},"institutions":[{"id":"https://openalex.org/I198945027","display_name":"Central European University","ror":"https://ror.org/02zx40v98","country_code":"AT","type":"education","lineage":["https://openalex.org/I198945027"]},{"id":"https://openalex.org/I51601045","display_name":"University of Bath","ror":"https://ror.org/002h8g185","country_code":"GB","type":"education","lineage":["https://openalex.org/I51601045"]}],"countries":["AT","GB"],"is_corresponding":false,"raw_author_name":"Tiago P. Peixoto","raw_affiliation_strings":["Department of Mathematical Sciences, University of Bath, Claverton Down, BA2 7AY, Bath, United Kingdom","Department of Network and Data Science, Central European University, Quellenstra\u00dfe 51, 1100, Vienna, Austria"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Mathematical Sciences, University of Bath, Claverton Down, BA2 7AY, Bath, United Kingdom","institution_ids":["https://openalex.org/I51601045"]},{"raw_affiliation_string":"Department of Network and Data Science, Central European University, Quellenstra\u00dfe 51, 1100, Vienna, Austria","institution_ids":["https://openalex.org/I198945027"]}]},{"author_position":"last","author":{"id":null,"display_name":"Eduardo G. Altmann","orcid":"https://orcid.org/0000-0002-1932-3710"},"institutions":[{"id":"https://openalex.org/I129604602","display_name":"The University of Sydney","ror":"https://ror.org/0384j8v12","country_code":"AU","type":"education","lineage":["https://openalex.org/I129604602"]}],"countries":["AU"],"is_corresponding":false,"raw_author_name":"Eduardo G. Altmann","raw_affiliation_strings":["School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia"],"raw_orcid":"https://orcid.org/0000-0002-1932-3710","affiliations":[{"raw_affiliation_string":"School of Mathematics and Statistics, The University of Sydney, NSW, 2006, Sydney, Australia","institution_ids":["https://openalex.org/I129604602"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I129604602"],"apc_list":{"value":1190,"currency":"GBP","value_usd":1459},"apc_paid":{"value":1190,"currency":"GBP","value_usd":1459},"fwci":1.8377,"has_fulltext":true,"cited_by_count":19,"citation_normalized_percentile":{"value":0.85697161,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":"10","issue":"1","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.30390000343322754,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.30390000343322754,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.09449999779462814,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10637","display_name":"Advanced Clustering Algorithms Research","score":0.05660000070929527,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6953999996185303},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.6241999864578247},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.6220999956130981},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5899999737739563},{"id":"https://openalex.org/keywords/node","display_name":"Node (physics)","score":0.5705000162124634},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4293999969959259},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.4293000102043152},{"id":"https://openalex.org/keywords/complex-network","display_name":"Complex network","score":0.4113999903202057}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8129000067710876},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6953999996185303},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.6241999864578247},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.6220999956130981},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5899999737739563},{"id":"https://openalex.org/C62611344","wikidata":"https://www.wikidata.org/wiki/Q1062658","display_name":"Node (physics)","level":2,"score":0.5705000162124634},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.5263000130653381},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4293999969959259},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.4293000102043152},{"id":"https://openalex.org/C34947359","wikidata":"https://www.wikidata.org/wiki/Q665189","display_name":"Complex network","level":2,"score":0.4113999903202057},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.39399999380111694},{"id":"https://openalex.org/C177937566","wikidata":"https://www.wikidata.org/wiki/Q4223102","display_name":"Document clustering","level":3,"score":0.39149999618530273},{"id":"https://openalex.org/C99844830","wikidata":"https://www.wikidata.org/wiki/Q102441924","display_name":"Scaling","level":2,"score":0.3806999921798706},{"id":"https://openalex.org/C138958017","wikidata":"https://www.wikidata.org/wiki/Q190087","display_name":"Data type","level":2,"score":0.35740000009536743},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.3522000014781952},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33640000224113464},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.31709998846054077},{"id":"https://openalex.org/C2775997480","wikidata":"https://www.wikidata.org/wiki/Q586277","display_name":"Degree (music)","level":2,"score":0.3109000027179718},{"id":"https://openalex.org/C2781170535","wikidata":"https://www.wikidata.org/wiki/Q30587856","display_name":"Noisy data","level":2,"score":0.29589998722076416},{"id":"https://openalex.org/C43596424","wikidata":"https://www.wikidata.org/wiki/Q98124957","display_name":"Probability and statistics","level":2,"score":0.29269999265670776},{"id":"https://openalex.org/C2777299769","wikidata":"https://www.wikidata.org/wiki/Q3707858","display_name":"Type (biology)","level":2,"score":0.28630000352859497},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.27399998903274536},{"id":"https://openalex.org/C22047676","wikidata":"https://www.wikidata.org/wiki/Q898680","display_name":"Clustering coefficient","level":3,"score":0.2630999982357025},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.25429999828338623}],"mesh":[],"locations_count":4,"locations":[{"id":"doi:10.1140/epjds/s13688-021-00288-5","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00288-5","pdf_url":"https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds/s13688-021-00288-5","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2106.15821","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2106.15821","pdf_url":"https://arxiv.org/pdf/2106.15821","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:doaj.org/article:4b9e5123e3de42f9a6295b26d8443f1d","is_oa":true,"landing_page_url":"https://doaj.org/article/4b9e5123e3de42f9a6295b26d8443f1d","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"EPJ Data Science, Vol 10, Iss 1, Pp 1-16 (2021)","raw_type":"article"},{"id":"pmh:oai:https://openresearch.ceu.edu:20.500.14018/28284","is_oa":true,"landing_page_url":"https://hdl.handle.net/20.500.14018/28284","pdf_url":null,"source":{"id":"https://openalex.org/S4306401981","display_name":"Open Research (Auckland University of Technology)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I39854758","host_organization_name":"Auckland University of Technology","host_organization_lineage":["https://openalex.org/I39854758"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"1","raw_type":"Journal article"}],"best_oa_location":{"id":"doi:10.1140/epjds/s13688-021-00288-5","is_oa":true,"landing_page_url":"https://doi.org/10.1140/epjds/s13688-021-00288-5","pdf_url":"https://epjdatascience.springeropen.com/counter/pdf/10.1140/epjds/s13688-021-00288-5","source":{"id":"https://openalex.org/S2504380752","display_name":"EPJ Data Science","issn_l":"2193-1127","issn":["2193-1127"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"EPJ Data Science","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320320966","display_name":"University of Sydney","ror":"https://ror.org/0384j8v12"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3173187313.pdf","grobid_xml":"https://content.openalex.org/works/W3173187313.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W745973578","https://openalex.org/W1578733506","https://openalex.org/W1666636243","https://openalex.org/W1927727507","https://openalex.org/W1930572491","https://openalex.org/W1972675431","https://openalex.org/W1981467090","https://openalex.org/W1994321911","https://openalex.org/W2012662151","https://openalex.org/W2054658115","https://openalex.org/W2090372231","https://openalex.org/W2093605115","https://openalex.org/W2102907934","https://openalex.org/W2119998616","https://openalex.org/W2127048411","https://openalex.org/W2157082398","https://openalex.org/W2169148563","https://openalex.org/W2174706414","https://openalex.org/W2205640179","https://openalex.org/W2273382362","https://openalex.org/W2394930177","https://openalex.org/W2411742801","https://openalex.org/W2525708387","https://openalex.org/W2531871281","https://openalex.org/W2552870695","https://openalex.org/W2742276251","https://openalex.org/W2811295899","https://openalex.org/W3003992897","https://openalex.org/W3011393870","https://openalex.org/W3037826211","https://openalex.org/W3123545922"],"related_works":[],"abstract_inverted_index":{"Abstract":[0],"We":[1,105,129],"are":[2],"interested":[3],"in":[4,14,20,138],"the":[5,21,29,65,71,86,90,93,108,125,133,173],"widespread":[6],"problem":[7],"of":[8,17,23,31,37,55,74,96,116,127,135,142,146,151,160],"clustering":[9],"documents":[10,19],"and":[11,25,48,122,131,149,169,171],"finding":[12],"topics":[13],"large":[15],"collections":[16],"written":[18],"presence":[22],"metadata":[24],"hyperlinks.":[26],"To":[27],"tackle":[28],"challenge":[30],"accounting":[32],"for":[33],"these":[34],"different":[35,72,97,139],"types":[36,99,159],"datasets,":[38],"we":[39],"propose":[40],"a":[41,163],"novel":[42],"framework":[43,69],"based":[44],"on":[45,167],"Multilayer":[46],"Networks":[47],"Stochastic":[49],"Block":[50],"Models.":[51],"The":[52,77],"main":[53],"innovation":[54],"our":[56,136],"approach":[57],"over":[58],"other":[59,81],"techniques":[60],"is":[61,85,111],"that":[62,107,154],"it":[63],"applies":[64],"same":[66],"non-parametric":[67],"probabilistic":[68],"to":[70,80,113,175],"sources":[73],"datasets":[75,140],"simultaneously.":[76],"key":[78],"difference":[79],"multilayer":[82],"complex":[83],"networks":[84],"strong":[87],"unbalance":[88],"between":[89],"layers,":[91],"with":[92,102],"average":[94],"degree":[95],"node":[98],"scaling":[100],"differently":[101],"system":[103],"size.":[104],"show":[106],"latter":[109],"observation":[110],"due":[112],"generic":[114],"properties":[115],"text,":[117],"such":[118],"as":[119],"Heaps\u2019":[120],"law,":[121],"strongly":[123],"affects":[124],"inference":[126],"communities.":[128],"present":[130],"discuss":[132],"performance":[134],"method":[137],"(hundreds":[141],"Wikipedia":[143],"documents,":[144],"thousands":[145,150],"scientific":[147],"papers,":[148],"E-mails)":[152],"showing":[153],"taking":[155],"into":[156],"account":[157],"multiple":[158],"information":[161],"provides":[162],"more":[164],"nuanced":[165],"view":[166],"topic-":[168],"document-clusters":[170],"increases":[172],"ability":[174],"predict":[176],"missing":[177],"links.":[178]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2021-07-05T00:00:00"}